US supercomputer unlocks nuclear salt reactor secrets with AI power

Scientists at Oak Ridge National Laboratory (ORNL) have developed a novel artificial intelligence (AI) framework that models the behavior of molten lithium chloride with quantum-level accuracy but in a fraction of the time required by traditional methods. Utilizing the Summit supercomputer, the machine-learning model predicts key thermodynamic properties of the salt in both liquid and solid states by training on a limited set of first-principles data. This approach dramatically reduces computational time from days to hours while maintaining high precision, addressing a major challenge in nuclear engineering related to understanding molten salts at extreme reactor temperatures. Molten salts are critical for advanced nuclear reactors as coolants, fuel solvents, and energy storage media due to their stability at high temperatures. However, their complex properties—such as melting point, heat capacity, and corrosion behavior—are difficult to measure or simulate accurately. ORNL’s AI-driven method bridges the gap between fast but less precise molecular dynamics and highly accurate but computationally expensive quantum simulations. This breakthrough enables faster, more reliable